You should build a data analytics project in a Jupyter notebook. In particular, you should do the following:
import pandas as pd
import plotly
import plotly.express as px
import plotly.graph_objects as go
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
canada = df[df["country"]=="Canada"]
canada.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 240 | Canada | Americas | 1952 | 68.75 | 14785584 | 11367.16112 | CAN | 124 |
| 241 | Canada | Americas | 1957 | 69.96 | 17010154 | 12489.95006 | CAN | 124 |
| 242 | Canada | Americas | 1962 | 71.30 | 18985849 | 13462.48555 | CAN | 124 |
| 243 | Canada | Americas | 1967 | 72.13 | 20819767 | 16076.58803 | CAN | 124 |
| 244 | Canada | Americas | 1972 | 72.88 | 22284500 | 18970.57086 | CAN | 124 |
import plotly.express as px
df = px.data.gapminder().query("country=='Canada'")
fig = px.line(df, x="year", y="pop", title='Population in Canada')
fig.show()
import plotly.express as px
df = px.data.gapminder().query("continent=='Europe'")
fig = px.line(df, x="year", y="pop", color='country')
fig.show()
import plotly.express as px
df = px.data.gapminder()
fig = px.scatter(df.query("year==2007"), x="gdpPercap", y="lifeExp",
size="pop", color="continent",
hover_name="country", log_x=True, size_max=60)
fig.show()
import plotly.express as px
df = px.data.gapminder().query("year == 2007").query("continent == 'Europe'")
df.loc[df['pop'] < 2.e6, 'country'] = 'Other countries' # Represent only large countries
fig = px.pie(df, values='pop', names='country', title='Population of European continent')
fig.show()
import plotly.express as px
# This dataframe has 244 lines, but 4 distinct values for `day`
df = px.data.gapminder().query("continent == 'Asia'").query("year==2007")
fig = px.pie(df, values='pop', names='country', title='Population of Asia in 2007')
fig.show()
import plotly.express as px
df = px.data.gapminder().query("continent == 'Asia'")
fig = px.area(df, x="year", y="pop")
fig.show()
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